University Of Tasmania

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On the application of near accident data to risk analysis of major accidents

journal contribution
posted on 2023-05-19, 08:43 authored by Khakzad, N, Faisal KhanFaisal Khan, Paltrinieri, N
Major accidents are low frequency high consequence events which are not well supported by conventional statistical methods due to data scarcity. In the absence or shortage of major accident direct data, the use of partially related data of near accidents - accident precursor data - has drawn much attention. In the present work, a methodology has been proposed based on hierarchical Bayesian analysis and accident precursor data to risk analysis of major accidents. While hierarchical Bayesian analysis facilitates incorporation of generic data into the analysis, the dependency and interaction between accident and near accident data can be encoded via a multinomial likelihood function. We applied the proposed methodology to risk analysis of offshore blowouts and demonstrated its outperformance compared to conventional approaches. © 2014 Elsevier Ltd. All rights reserved.


Publication title

Reliability Engineering and System Safety








Australian Maritime College


Elsevier B.V.

Place of publication

United Kingdom

Rights statement

Copyright 2014 Elsevier Ltd. All rights reserved.

Repository Status

  • Restricted

Socio-economic Objectives

Expanding knowledge in engineering